Hardware-ased parallel computing tools for realtime haptic and deformation rendering of soft objects

通过融合视觉、动觉和力反馈等感知方式，交互式虚拟现实模拟器正变得越来越逼真。在涉及生物软组织的医疗应用中，经常会发生与非刚性可变形物体的相互作用。虽然这些相互作用的基于物理的数学建模已经取得了很大的进展，但这些模型在实时仿真中的实际应用仍然受到限制，主要是因为它们的计算复杂性。具体地说，具有触觉反馈的应用程序需要非常高的模拟更新率来保持系统的稳定性，从而施加了超出现有单处理器计算机能力的严格的时间限制。基于我们以前在触觉方面的工作，本研究探索了一种新的并行计算范式，用于实时高保真地模拟包含视觉和触觉反馈的软对象交互。将开发定制的计算工具，这些工具同时使用数千个处理单元来求解由软对象变形的有限元模型产生的大型稀疏方程系统。该解将以足够高的更新率获得，以保证模拟的稳定性和保真度。这些计算工具本质上将是在使用现场可编程门阵列(FPGA)技术的合成硬件架构上递归方程解算器的并行实现。在多个互连的FPGA芯片上进行大规模并行计算将在廉价和紧凑的封装中提供巨大的计算能力，从而能够模拟高保真的软组织变形模型。这项研究的结果将有助于开发下一代计算机辅助外科系统和医学培训模拟器。将由此产生的核心计算技术整合到这样的系统中，将在计算机辅助医疗培训、诊断以及医疗干预的规划和执行方面创造更好的和新的业务能力。其他需要稀疏线性方程组快速解的科学应用也将从这项研究中受益。

Interactive virtual reality simulators are becoming increasingly realistic by incorporating sensing modalities such as vision, kinesthesia and force feedback, also known as haptics. Interactions with non-rigid deformable objects often occur in medical applications involving biological soft-tissue. While a great deal of progress has been made in physics-based mathematical modeling of these interactions, practical applications of such models in real-time simulations have remained limited mainly due to their computational complexity. In particular, applications with haptic feedback would require very high simulation update rates to maintain the system stability, imposing strict timing constraints beyond the capabilities of existing single-processor computers. Building upon our previous work in haptics, this research explores a new paradigm in parallel computing for real-time high-fidelity simulation of soft-object interaction involving visual and haptic feedback. Customized computing tools will be developed that concurrently employ thousands of processing units to solve a large sparse system of equations arising from the finite element models of soft-object deformation. The solution will be obtained at sufficiently high update rates for simulation stability and fidelity. These computing tools will be essentially parallel implementations of recursive equation solvers on synthesized hardware architectures using the Field-Programmable Gate Array (FPGA) technology. Massive parallelization of the computations on multiple interconnected FPGA chips will provide enormous computing power in an inexpensive and compact package enabling the simulation of high-fidelity soft-tissue deformation models. The results of this research will be instrumental in the development of the next generation of computer-assisted surgical systems and medical training simulators. The integration of the resulting core computational technologies into such systems will create improved and new operational capabilities in computer-assisted medical training, diagnosis, and planning and execution of medical interventions. Other scientific applications requiring fast solutions to sparse linear systems of equations will also benefit from this research.